National Taiwan University of Science and Technology

Multifunctional Materials Manufacturing Laboratory

Jung-Ting Tsai
https://sites.google.com/view/tsaij/%E9%A6%96%E9%A0%81

Research Field

Materials Engineering

Introduction

Dr. Jung-Ting Tsai is currently an assistant professor in the Mechanical Department at the National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan (R.O.C.). He was a post-doc in the Applied Materials Division at Argonne National Laboratory, Lemont, IL, USA, from 2022 to 2023. He received his Ph.D. in Materials Engineering from Purdue University, West Lafayette, IL, USA in 2021. In addition, he has two master's degrees, one at Purdue University, received in 2018, and another at NTUST, which he received in 2012. His research focuses on three major areas: additive manufacturing ceramic materials, cold spray repair and coating, and materials health monitoring. His lead author on the cold spray manuscript has been selected as an Editor's Choice article by the Journal of Thermal Spray Technology in 2021. In addition, he is the recipient of the International Thermal Spray Association Graduate Scholarship. His paper on structural health monitoring was selected as the 2nd best manuscript by the Society of Plastics Engineering in 2018.

A strongly driven consent for sustainable, renewable, and carbon-free manufacturing processes has progressed throughout the upcoming years. This is mainly because drastic climate change has undeniably altered our daily lives, from abnormal temperature fluctuation to limited accessibility of energy resources. Therefore, a continuation of a more cost-effective and scalable manufacturing process has been proposed to combat the swift challenges.

My research area focuses on additive manufacturing (AM), material repair operations (MRO), and structural health monitoring (SHM). The lab will focus on these three main topics and continue seeking resources from industry sponsors and academic financial support. My research focuses on the additive manufacturing of refractory ceramic materials while using cold spray as a tool for repairing/modifying the surface and increasing engineering property performances. In addition, material structural health monitoring via fiber optical sensing is also embedded in the manufactured parts for in-situ onsite monitoring. The combined proposed technology (AM, MRO, and SHM) promotes design flexibility while maximizing engineering performance with time and energy efficiency. This will pave the pathway for the novel "Next Generation" of materials and manufacturing. The technology has many potential applications, such as semiconductor packaging, aerospace components, microwaving heat conservation, (heat) waste collection, recuperators, etc. Furthermore, the proposed technology will have a widespread impact on the decarbonization of minimizing/eliminating the use of fossil fuels.


Research Topics

Additive manufacturing, Cold spray coating, Composite materials, Non-destructive testing (NDT), Structural health monitoring (SHM), CFRP fabrication, Polymer testing


Honor
  • Establishing a Cold Spray Particle Deposition Window on Polymer Substrate: Editor’s Choice article by the Journal of Thermal Spray Technology, 2021
  • Estus H. and Vashti L. Magoon Award for Excellence in Teaching, 2021
  • International Thermal Spray Association Graduate Scholarship, 2020
  • 2nd best paper award for Integrated Structural Monitoring of Composite Materials via Distributed Optical Sensor in Society of Plastics Engineers- Automotive & Composites Divisions, 2018 
  • Honorary Member of the Phi Tau Phi Scholastic Society, 2012

Educational Background

Ph.D., Materials Engineering, Purdue University, West Lafayette, IN , 2021

M.S., Materials Engineering, Purdue University, West Lafayette, IN, 2018

M.S., Mechanical Engineering, National Taiwan University of Science and Technology, Taiwan, 2012

B.S., Materials Engineering, Tatung University, Taiwan, 2010


2 Vacancies

Job Description

Design and simulation in additive manufacturing equipped with data-driven modeling skills (such as machine learning). Basic computer coding skills are required (Python or C++). Student experience with finite element analysis is encouraged.

Preferred Intern Education Level

Undergraduate engineering students or above degree

Skill sets or Qualities

  • Take initiative.
  • Able to work independently.
  • Meet deadlines.
  • Identify areas for improvement.
  • Solve problems.
  • Exceed expectations.